High-Throughput Data Processing Architectures on AWS for Logistics and Transportation Systems

Authors

  • Mohammed Abdul Mannan Ansari Independent Researcher, USA. Author

DOI:

https://doi.org/10.63282/3050-9246.IJETCSIT-V7I1P144

Keywords:

AWS, High-Throughput Processing, Logistics Systems, Stream Processing, Batch Processing, Amazon Kinesis, Scalability, Iot Data Processing

Abstract

Modern logistics and transportation systems generate massive volumes of data from IoT sensors, GPS trackers, fleet management systems, and supply chain operations. This White paper presents comprehensive architectural patterns for implementing high-throughput data processing systems on Amazon Web Services (AWS) that handle both streaming and batch workloads. The proposed architectures leverage AWS services, including Amazon Kinesis Data Streams, AWS Lambda, and Amazon EMR to provide scalable, reliable, and cost-effective solutions. Key focus areas include real-time streaming processing for operational insights, batch processing for historical analysis, and fault tolerance mechanisms. Implementation patterns demonstrate processing capabilities exceeding 50,000 messages per second while maintaining sub-second latency for critical logistics operations.

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References

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Published

2026-03-13

Issue

Section

Articles

How to Cite

1.
Mannan Ansari MA. High-Throughput Data Processing Architectures on AWS for Logistics and Transportation Systems. IJETCSIT [Internet]. 2026 Mar. 13 [cited 2026 Jul. 30];7(1):300-4. Available from: https://ijetcsit.org/index.php/ijetcsit/article/view/639

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